Principal Instructor

Dr. POH, Kim Leng

Associate Professor

Department of Industrial Systems Engineering & Management

National University of Singapore.

email: pohkimleng@nus.edu.sg | website | facebook

office: E1A-06-10 | phone: 6516 2193

Course Descriptions

IE4243 (4 units). This course teaches the necessary analytical knowledge and practical skills for improving decision-making processes in engineering, management and business environments. This is achieved by providing a paradigm based on normative decision theory and a set of prescriptive tools and computational techniques using state-of-the art software with which a stake holder can systematically analyze a complex and uncertain decision situation leading to clarity of action. Topics from utility theory, influence diagrams, risk preference to multi-attribute utility theory and analytic hierarchy process are covered.

Course Outline

1. Introduction to Decision Analysis
2. Modeling Uncertainty
3. Decision Theory
4. Basic Decision Analysis: Decision Tree, Sensitivity Analysis, Value of Information, Stochastic Dominance
5. Decision Modeling and Analysis using Bayesian Networks and Influence Diagrams
6. Advanced Decision Analysis: Risk Preferences
7. Probability Distribution Assessment
8. Complex Decision Problems: The Decision Analysis Process/Cycle
9. MCDM I: Analytic Hierarchy Process (AHP)
10. MCDM II: Multi-Attribute Utility Theory and Trade-off Analysis
11. Software: DPL, Netica, YAAHP, Excel, Python

Learning Outcomes

Upon completion of this course you will be able to:

1. Use probability trees to model uncertain events and deal with new information.
2. Apply the rules or axioms of decision theory to decision situations involving uncertainty.
3. Perform decision analysis using tools such as decision tree, Bayesian networks or influence diagrams, including sensitivity and value of information analysis.
4. Perform decision analysis under different risk attitudes and degree of risk aversions.
5. Assess probability distributions from experts and/or data.
6. Use the Analytic Hierarchy Process (AHP) for decision making under multiple criteria.
7. Develop and analyze complex decision problems and scenarios that require use of a combination of the methods above.
8. Perform integrated analysis using selected professional decision analysis software.

Assessments

• Assignments: 5%
• Mid Term: 20%
• Project: 25%
• Final Exam: 50%

Group Project

Students will work in group to work on the application of decision analysis to a realistic real-world problem using techniques and software learned in this course.

Homeworks

Homework exercises are given at the end of each chapter in the lecture notes. They will not be graded.

You are required to attempt them as they will help you understand the class materials better.

Solutions will provided.

Required Readings

• K.L. Poh, Decision Modeling and Risk Analysis Lecture Notes.

References

1. R.T. Clemen and T. Reilly, Making hard decisions with DecisionTools, 3rd Edition, Duxbury Thomson Learning, 2014.
2. R.A. Howard and J.E. Matheson (Editors), Readings on the Principles and Applications of Decision Analysis, Strategic Decision Group, Vol. I and II, 1983.
3. T.L. Saaty, The Analytic Hierarchy Process, McGraw Hill, New York, 1980 (RWS edition 1990).
4. R.L. Keeney and H. Raiffa, Decisions with Multiple Objectives: Preferences and Value Tradeoffs, 1975.